fork/cellxgene
1
0
Fork 0
mirror of https://github.com/chanzuckerberg/cellxgene.git synced 2026-10-03 14:38:11 +08:00
Code Issues Packages Projects Releases Wiki Activity

TS migration. #2288. (#2328)

Browse Source 
* Added TS. Updated build and linting config. Added types.

* [ts-migrate][.] Rename files from JS/JSX to TS/TSX

Co-authored-by: ts-migrate <>

* [ts-migrate][.] Run TS Migrate

Co-authored-by: ts-migrate <>

* Corrected files mangled by ts-migrate.

* Updated lint config, minor linting.

* Re-enabled Husky.

* Updated tests and config.

* Reverted webpack devtool config.

* Removed obsolete snapshots.

* Added annotations snap.

* Updated tsconfig includes wrt linting.

* Removed ts-migrate.

Co-authored-by: Timmy Huang <tihuan@users.noreply.github.com>
This commit is contained in:
Mim Hastie
2021-07-26 20:18:17 +00:00
committed by GitHub
co-authored by ts-migrate Timmy Huang
parent 7328cbdbd5
commit 934cc5c69b
206 changed files with 4719 additions and 2085 deletions
Download Patch File Download Diff File Expand all files Collapse all files
client/__tests__/util/dataframe/summarize.test.js
-281
View File
@@ -1,281 +0,0 @@
import * as Dataframe from "../../../src/util/dataframe";
function float32Conversion(f) {
return new Float32Array([f])[0];
}
describe("Dataframe column summary", () => {
test("empty column test", () => {
const df = Dataframe.Dataframe.create([0, 1], [[]]);
const summary = df.icol(0).summarize();
expect(summary).toEqual(
expect.objectContaining({
categorical: true,
categories: [],
categoryCounts: new Map(),
numCategories: 0,
})
);
});
test("simple test", () => {
const df = new Dataframe.Dataframe(
[1, 6],
[
["n1"],
["hi"],
[true],
new Float32Array([39.3]),
new Int32Array([99]),
[1],
],
null,
new Dataframe.KeyIndex([
"name",
"nameString",
"nameBoolean",
"nameFloat32",
"nameInt32",
"nameCategorical",
])
);
expect(df.icol(0).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: ["n1"],
categoryCounts: new Map([["n1", 1]]),
numCategories: 1,
})
);
expect(df.icol(1).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: ["hi"],
categoryCounts: new Map([["hi", 1]]),
numCategories: 1,
})
);
expect(df.icol(2).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: [true],
categoryCounts: new Map([[true, 1]]),
numCategories: 1,
})
);
expect(df.icol(3).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: float32Conversion(39.3),
max: float32Conversion(39.3),
nan: 0,
ninf: 0,
pinf: 0,
})
);
expect(df.icol(4).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: 99,
max: 99,
nan: 0,
ninf: 0,
pinf: 0,
})
);
expect(df.icol(5).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: [1],
categoryCounts: new Map([[1, 1]]),
numCategories: 1,
})
);
});
test("multi test", () => {
const df = new Dataframe.Dataframe(
[3, 6],
[
["n0", "n1", "n2"],
["hi", "hi", "bye"],
[false, true, true],
new Float32Array([39.3, 39.3, 0]),
new Int32Array([99, 99, 99]),
[1, false, "0"],
],
null,
new Dataframe.KeyIndex([
"name",
"nameString",
"nameBoolean",
"nameFloat32",
"nameInt32",
"nameCategorical",
])
);
expect(df.icol(0).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining(["n0", "n1", "n2"]),
categoryCounts: new Map([
["n0", 1],
["n1", 1],
["n2", 1],
]),
numCategories: 3,
})
);
expect(df.icol(1).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining(["hi", "bye"]),
categoryCounts: new Map([
["hi", 2],
["bye", 1],
]),
numCategories: 2,
})
);
expect(df.icol(2).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining([true, false]),
categoryCounts: new Map([
[true, 2],
[false, 1],
]),
numCategories: 2,
})
);
expect(df.icol(3).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: 0,
max: float32Conversion(39.3),
nan: 0,
ninf: 0,
pinf: 0,
})
);
expect(df.icol(4).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: 99,
max: 99,
nan: 0,
ninf: 0,
pinf: 0,
})
);
expect(df.icol(5).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining([1, false, "0"]),
categoryCounts: new Map([
[1, 1],
[false, 1],
["0", 1],
]),
numCategories: 3,
})
);
});
test("non-finite numbers", () => {
const df = new Dataframe.Dataframe(
[4, 6],
[
["n0", "n1", "n2", "n2"],
["hi", "hi", "bye", "bye"],
[false, true, true, true],
new Float32Array([
39.3,
Number.NEGATIVE_INFINITY,
Number.NaN,
Number.POSITIVE_INFINITY,
]),
new Int32Array([99, 99, 99, 99]),
[1, false, "0", "0"],
],
null,
new Dataframe.KeyIndex([
"name",
"nameString",
"nameBoolean",
"nameFloat32",
"nameInt32",
"nameCategorical",
])
);
expect(df.icol(0).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining(["n0", "n1", "n2"]),
categoryCounts: new Map([
["n0", 1],
["n1", 1],
["n2", 2],
]),
numCategories: 3,
})
);
expect(df.icol(1).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining(["hi", "bye"]),
categoryCounts: new Map([
["hi", 2],
["bye", 1],
]),
numCategories: 2,
})
);
expect(df.icol(2).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining([true, false]),
categoryCounts: new Map([
[true, 2],
[false, 1],
]),
numCategories: 2,
})
);
expect(df.icol(3).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: float32Conversion(39.3),
max: float32Conversion(39.3),
nan: 1,
ninf: 1,
pinf: 1,
})
);
expect(df.icol(4).summarize()).toEqual(
expect.objectContaining({
categorical: false,
min: 99,
max: 99,
nan: 0,
ninf: 0,
pinf: 0,
})
);
expect(df.icol(5).summarize()).toEqual(
expect.objectContaining({
categorical: true,
categories: expect.arrayContaining([1, false, "0"]),
categoryCounts: new Map([
[1, 1],
[false, 1],
["0", 1],
]),
numCategories: 3,
})
);
});
});